qphen: Quantum Phenotype Interactions in HIV Model

In qvirus: Quantum Computing for Analyzing CD4 Lymphocytes and Antiretroviral Therapy

Quantum Phenotype Interactions in HIV Model

Description

The qphen dataset contains 176 observations and 24 variables, representing classified phenotype interactions in a quantum game-theoretic model of HIV phenotypes. The data includes CD4 and viral load differences, quantum game strategies, classification clusters, and tuberculosis/genoresistance indicators.

Usage

data(qphen)

Format

A data frame with 176 rows and 24 variables:

id

(double) Unique identifier for each observation.

vl_diff

(double) Difference in viral load (log scale) between time points.

cd_diff

(double) Difference in CD4 count between time points.

vlogs_diff_mean

(double) Mean difference of viral loads across the dataset.

cds_diff_mean

(double) Mean difference of CD4 counts across the dataset.

n

(double) Number of cases in each interaction cluster.

payoffs

(double) Computed payoff for the phenotype interaction.

#'

payoffs_b

(double) Alternative computed payoff.

nearest_payoff

(double) Closest estimated payoff value.

classification_2

(double) Cluster assignment for phenotype interactions (second clustering method).

classification_3

(double) Cluster assignment for phenotype interactions (third clustering method).

classification_4

(double) Cluster assignment for phenotype interactions (fourth clustering method).

phen_1

(double) Phenotype type (v or V).

str1_2

(double) Strategy of the first phenotype using X, T, or H gate (binary encoding).

str1_3

(double) Alternative strategy of the first phenotype.

str2_2

(double) Strategy of the second phenotype using H, Id, S, T, X, Y, or Z gate (binary encoding).

str2_3

(double) Alternative strategy of the second phenotype.

str2_4

(double) Alternative strategy of the second phenotype.

str2_5

(double) Alternative strategy of the second phenotype.

str2_6

(double) Alternative strategy of the second phenotype.

str2_7

(double) Alternative strategy of the second phenotype.

batch_1

(double) Indicates whether predictions were made on full data or batch data.

TB_1

(double) Indicator for tuberculosis presence (1 = TB, 0 = no TB).

GR_1

(double) Indicator for genoresistance presence (1 = resistant, 0 = non-resistant).

Examples

data(qphen)
head(qphen)

qvirus documentation built on June 8, 2025, 10:06 a.m.